Fill-Mask
Transformers
Safetensors
bert
masked-lm
bytecode
genetic-improvement
genetic-programming
mutation
Instructions to use lucapernice/BERT-Bytecode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lucapernice/BERT-Bytecode with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lucapernice/BERT-Bytecode")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lucapernice/BERT-Bytecode") model = AutoModelForMaskedLM.from_pretrained("lucapernice/BERT-Bytecode") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 815e0fd40b2e54790dae84a5f3292b77bb3ae900af7376edbf95eb790ab86de7
- Size of remote file:
- 344 MB
- SHA256:
- 55b5a1665347190e67f7a198c0540021faebb3a9b64e38b8c9dd18e81c347570
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